Comparison of the learning curve of robot -assisted and laparoscopic -assisted gastrectomy.
10.11817/j.issn.1672-7347.2023.220635
- Author:
Jingmao XIE
1
;
Yang LEI
2
;
Hao ZHANG
2
;
Yihui LIU
2
;
Bo YI
3
,
4
Author Information
1. Second Department of Gastrointestinal, Third Xiangya Hospital, Central South University, Changsha 410013, China. 294429253@qq.com.
2. Second Department of Gastrointestinal, Third Xiangya Hospital, Central South University, Changsha 410013, China.
3. Second Department of Gastrointestinal, Third Xiangya Hospital, Central South University, Changsha 410013, China. yibo2018pro@
4. com.
- Publication Type:Journal Article
- Keywords:
Da Vinci surgical robot system;
gastric cancer;
lymph adenectomy (D2);
robot-assisted gastrectomy
- MeSH:
Humans;
Robotics;
Robotic Surgical Procedures/methods*;
Learning Curve;
Stomach Neoplasms/pathology*;
Retrospective Studies;
Laparoscopy/methods*;
Lymph Node Excision/methods*;
Gastrectomy/methods*;
Treatment Outcome
- From:
Journal of Central South University(Medical Sciences)
2023;48(5):716-724
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:Da Vinci robot technology is widely used in clinic,with minimally invasive surgery development. This study aims to explore the possible influence of advanced surgical robotics on the surgery learning curve by comparing the initial clinical learning curves of 2 different surgical techniques: robotic-assisted gastrectomy (RAG) and laparoscopic-assisted gastrectomy (LAG).
METHODS:From September 2017 to December 2020, a chief surgeon completed a total of 108 cases of radical gastric cancer from the initial stage, including 27 cases of RAG of the Da Vinci Si robotic system (RAG group) and 81 cases of LAG (LAG group). The lymph node of gastric cancer implemented by the Japanese treatment guidelines of gastric cancer. The surgical results, postoperative complications, oncology results and learning curve were analyzed.
RESULTS:There was no significant difference in general data, tumor size, pathological grade and clinical stage between the 2 groups (P>0.05). The incidence of serious complications in the RAG group was lower than the LAG group (P=0.003). The intraoperative blood loss in the RAG group was lower than that in the LAG group (P=0.046). The number of lymph nodes cleaned in the RAG group was more (P=0.003), among which there was obvious advantage in lymph node cleaning in the No.9 group (P=0.038) and 11p group (P=0.015). The operation time of the RAG group was significantly longer than the LAG group (P=0.015). The analysis of learning curve found that the cumulative sum analysis (CUSUM) value of the RAG group decreased from the 10th case, while the CUSUM of the LAG group decreased from the 28th case. The learning curve of the RAG group had fewer closing cases than that of the LAG group. The unique design of the surgical robot might help to improve the surgical efficiency and shorten the surgical learning curve.
CONCLUSIONS:Advanced robotics helps experienced surgeons quickly learn to master RAG skills. With the help of robotics, RAG are superior to LAG in No.9 and 11p lymph node dissection and surgical trauma reduction. RAG can clear more lymph nodes than LAG, and has better perioperative effect.
